Representation of modern pollen assemblages with respect to vegetation and climate in Northeast China

Abstract

The characterization of modern pollen–vegetation–climate relationships forms the basis of past environmental and climatic reconstructions from fossil pollen records. Northeast China, which is located in a high-latitude temperate zone, is an ideal area for investigating the relationship between modern pollen assemblages and climate. However, a scarcity of datasets and detailed research on surface pollen in Northeast China prohibits high-resolution quantitative climate reconstructions in China. Here, a total of 43 surface moss samples from forest regions in the eastern part of Northeast China were collected and analyzed for pollen content. The pollen-vegetation-climate relationship was investigated by calculating distance-weighted vegetation abundances, cluster analysis, indicator species analysis, ordination analysis, correlation analysis and biomization. Pollen assemblages were compared with vegetation types recorded at the sampling sites on different scales. The combination of cluster analysis, indicator species analysis and biomization identified which forest types the surface pollen assemblages represented. Our results showed that: 1) Surface pollen assemblages from the forest region of Northeast China can be used to distinguish mixed forest types from coniferous forest at a regional scale. Indicator taxa of coniferous forest include Alnus and Betula, while the indicator taxa of mixed forest are the combinations of Juglans, Tilia, Ulmus, Quercus and Pinus. 2) Principal Component Analysis (PCA) indicates that the pollen assemblages are mainly controlled by temperature and precipitation, while the mean temperature of the coldest month (Mtco) is the most significant factor controlling vegetation change. 3) The Betula/Quercus ratio drops dramatically from coniferous forest to mixed forest with an increasing Mtco and can thus be used as an indicator of vegetation types at a regional scale and as an index to reconstruct temperature.